Abstract

When evaluating Peer-to-Peer content distribution systems by means of simulation, it is of vital importance to correctly mimic the bandwidth dynamics behavior of the underlying network. In this paper, we propose a scalable and accurate flow-level network simulation model based on an evolution of the classical progressive filling algorithm which implements the max-min fairness idea. We build on top of the current state of art by applying an optimization to reduce the cost of each bandwidth allocation/deallocation operation on a node-based directed network model. Unlike other works, our evaluation of the chosen approach focuses both on efficiency and on accuracy. Our experiments show that, in terms of scalability, our bandwidth allocation algorithm outperforms existing directed models when simulating large-scale structured overlay networks. Whereas, in terms of accuracy we show that allocation dynamics of the proposed solution follow those of the NS-2 packet-level simulator by a small and nearly constant offset for the same scenarios. To the best of our knowledge, this is the first time that an accuracy study has been conducted on an improvement of the classical progressive filling algorithm.